Identification method of drought resistance on maize based on qRT-PCR

Background: In order to reveal the mechanism of drought resistance of maize, establish the molecular identification system of drought resistance and solve the problem of difficult identification of drought resistance of maize. Taking Nongdan 476, a drought-tolerant maize hybrid cultivar, and Zhongxin 978, a drought-sensitive maize hybrid cultivar, as materials, drought stress and normal watering treatment were carried out at seedling stage, flare stage, tasseling stage and filling stage, and leaf tissue were collected for transcriptomes. Results: P-vaule < 0.05 was selected as the screening standard. There were 6281, 17191, 21790 and 15475 differentially expressed genes of each stage, respectively. At the same time, only DnaJ gene was significantly differentially expressed at the four stages. The preliminary results of qRT-PCR showed that the up regulation of DnaJ gene expression was consistent with the results of transcriptome analysis. DnaJ gene expression was further detected by using control samples with specific drought resistance index of yield. The results showed that DnaJ gene expression drought resistance index (DI E ) was highly correlated with yield drought resistance index (DI P ), and the 5-level criteria for DnaJ gene expression drought resistance index (DI E ) were defined by their linear equations. Conclusion: Drought resistance of maize is a character controlled by multiple genes. There is a significant difference between the expression of DnaJ gene in drought resistant and non drought resistant maize, which has the potential to be used as molecular identification of drought resistance of maize, and can provide a more comprehensive and accurate technical means for drought resistance cultivation and breeding of maize.

serious [6]. Maize is the world's highest yield food crop. In 2012, the domestic maize production and planting area have exceeded rice and wheat, becoming the largest food crop in China [7]. Maize needs a lot of water in the whole growth period [8,9,10]. The shortage of water resources has a serious impact on the yield and quality of maize [11,12]. It is very urgent to establish the identification method of drought resistance in maize.
The drought resistance performance of maize is restricted by its own genetic effect and environmental factors. Due to the different growth and development period of crops, the influence of biological factors and non biological factors, so far any single drought resistance research has certain limitations, so it is difficult to directly and accurately evaluate the drought resistance of maize. There are many methods to identify the drought resistance of maize [13,14,15], including field direct identification method, artificial simulation environment method, physiological index method and molecular biological identification method. Among them, the field direct identification method is to identify the growth forms of crops in different growth and development periods, but these methods have the disadvantages of long time and environmental factors, especially the large interannual precipitation variation, which makes the research results difficult to repeat. The artificial simulated environment method is to regulate the soil and air in the arid shed, growth box or artificial climate chamber water content is the drought stress environment required by experiments. The method of evaluating the drought resistance of water maize by studying the growth and development of maize, physiological process or the change of yield results is needed. This method needs certain equipment, and the energy consumption is relatively large. The created drought stress environment is different from the field production under natural conditions, which results in the experiment results and the field production. There are some differences in the results of direct identification, physiological index method is mainly used to identify the drought resistance of plants, such as leaf water related indicators, plasma membrane permeability and enzyme activity. However, these physical and chemical indicators will change due to the different growth environment and growth period, and are also prone to errors due to the reagents used and human operation. Molecular biological identification method is based on modern molecular biology, the saturated molecular genetic map was constructed by using related molecular markers, and the drought resistance genes of maize were located. The drought resistance varieties were selected by using molecular markers. Drought resistance is a quantitative character controlled by multiple genes [16]. In recent years, many drought resistance QTLs were found, but the polymorphism frequency of the markers is very low, and a single QTL has little effect on the phenotypic difference, and the difficulty in evaluating epistasis effect. Further research is needed to use molecular marker assisted selection [17]. Therefore, it is urgent to establish new technologies and find new markers to solve these problems.
In recent years, with the rapid development of omics, transcriptomics has been applied in the field of crop drought resistance research , which provides a development direction for the discovery and screening of molecular markers for drought resistance identification of maize and improving the level of drought resistance identification.

Sample Total RNA Agarose Gel Electrophoresis Detection
Total RNA of 36 samples was isolated from non-stressed and stressed at seedling stage, flare stage, tasseling stage and filling stage of the two maize hybrid cultivar(Nongdan476 and Zhongxin978) and prepared for Agarose gel electrophoresis ( Fig.1). It can be seen in the figure that the total RNA electrophoresis bands of 36 samples are clear and bright, and the RNA integrity is good, which is suitable for transcriptome sequencing.

RNA-Sequencing (RNA Seq) Analysis
Total RNA isolated from non-stressed and stressed was used for the RNA-Seq transcriptome analysis. After filtering the sequencing results, a total of 2.03B clean data was generated from 36 samples. For the 36 samples, the bases with the quality value of clean data ≥ Q30 were higher than 95.95%, which proved the reliability of the sequencing results ( Table 1). The clean reads of each sample were mapped to the maize reference genome sequence(B73 RefGen_v3), the results showed that the mapping rates ranged from 84.69% to 93.23% (Table 1).

Differential Gene Expression Analysis
In order to determine the response of materials to drought, the transcriptome of the same cultivar in the same stage of drought and control treatment were analyzed for differential expression, and in order to explore the genetic differential expression genes of two extreme cultivars, the differential expression genes of two hybrid cultivars under the same water condition were analyzed. Therefore, four sets of differentially expressed genes can be obtained in each treatment stage, namely seedling stage: TC_TD, SC_SD, TC_SC, SD_TD; flare stage: TC1_vs_TD1, SC1_vs_SD1, TC1_vs_SC1 and SD1_vs_TD1; tasseling stage: TC2vs_TD2, SC2_vs_SD2, TC2_vs_SC2 and SD2_vs_TD2; filling stage: TC3_vs_TD3, SC3_vs_SD3, TC3_vs_SC3 and SD3_vs_TD3. With |log2(fold change)|>1 ， P-vaule<0.05 as the screening criteria, 6281, 17191, 21790 and 15475 differential genes were expressed at seedling stage, flare stage, tasseling stage and filling stage, respectively ( Fig. 2).

Screening of Marker Genes
When maize is under drought stress, there are up-regulated and down-regulated genes in different development stages and different strains (drought tolerance or sensitivity). Under the same moisture conditions, 4331, 6580, 8180 and 7477 differential genes were identified at seedling stage (TC_SC), flare stage (TC1_vs_SC1), tasseling stage (TC2_vs_SC2) and filling stage (TC3_vs_SC3) before drought treatment, respectively. After the drought treatment, 5398 differential genes were identified at seedling stage (SD_TD), 6282 differential genes were identified at flare stage (SD1_vs_TD1), 10091 differential genes were identified at tasseling stage (SD2_vs_TD2), and 7442 differential genes were identified at filling stage (SD3_vs_TD3). 129, 666, 2417, and 375 differential genes were identified in drought-resistant cultivar (Henong 476) at seedling stage (TC_TD), flare stage (TC1_vs_TD1), tasseling stage (TC2_vs_TD2), and filling stage (TC3_vs_TD3) before and after drought stress treatment. 754, 3663, 1102, and 181 differential genes were identified in the sensitive cultivar (Zhongxin978) at seedling stage (SC_SD), flare stage (SC1_vs_SD1), tasseling stage (SC2_vs_SD2), and filling stage (SC3_vs_SD3) before and after drought stress treatment (Fig. 3). In response to drought stress, some gene sets play a more important role. As shown in the figure, I, II, III and IV represent the differentially expressed genes of resistant cultivar-Henong 476 before and after drought treatment and the differentially expressed genes in response to drought stress in the two hybrid cultivars. Through analysis, we found that a differential gene zm00001d02666 was identified as a marker gene for co-expression during the four stages of drought treatment, which can be used to identify the drought resistance of Maize (Fig. 4). Moreover, heat maps were drawn for the expression of this differential gene in each group at four different stages. It could be found that the expression level of drought-resistant cultivar was higher than that of sensitive cultivar after drought stress (Fig. 5).

Verification of Expression Difference of DnaJ Marker Gene
The expression of DnaJ gene at seedling stage, flare stage, tasseling stage and filling stage was verified by using drought-resistant cultivar Nongdan 476 and drought-tolerant cultivar Zhongxin 978 (Fig. 6). It can be seen from Fig. 6 that the expression level of qRT-PCR of drought resistant cultivar Nongdan 476 was high at four stages, while that of non-drought resistant cultivar Zhongxin 978 was low at four stages. It is suggested that RNA-Seq of DnaJ gene is highly consistent with qRT-PCR.   Fig.7. According to the correlation coefficient r = 0.92 in Fig.7, the Significant correlation is reached (P < 0.01).  Table 3. According to table 3, the criteria of drought resistance index of expression quantity are as follows: ≥ 1.30 is extremely strong (HR); 1.11-1.29 is strong (R); 0.91-1.10 is medium (MR); 0.71-0.90 is weak (s); and ≤ 0.70 is extremely weak (HS)

Discussion
In this study, in order to explore the response of Maize to drought, we analyzed the transcriptome differential expression of drought stress and control treatment at seedling stage, flare stage, tasseling stage and filling stage. The results showed that the differential expression genes in seedling stage,flare stage, tasseling stage and filling stage were 6281, 17191, 21790, and 15475, respectively, Furthermore, drought resistance is a very complex quantitative trait controlled by multiple genes. The DnaJ gene (zm00001d02666) with significant difference in expression at four stages was screened through linkage analysis. The gene was preliminarily verified in drought resistant and non drought resistant maize by qRT-PCR. The result was up-regulated in drought resistant cultivars and significantly different from that of sensitive materials. This result was consistent with the result of transcriptome analysis, which further suggested that DnaJ gene could be used as drought resistant material The potential of the identified molecular marker. In addition, this study collected maize cultivars with different drought resistance that have been identified, and detected the expression level of DnaJ by qRT-PCR technology. The results showed that the expression level of DnaJ was significantly different in different drought resistant maize cultivars, and the expression level was positively correlated with the drought resistance index ID of different maize cultivars, and the difference was statistically significant, so it could be used as a marker for drought resistance identification of maize. DnaJ protein is a kind of protein in Hsp40 family. Its N-terminal contains a conserved J domain of about 70 amino acids, also known as J protein [18]. DnaJ protein can promote the ATPase activity of HSP70, and it is the chaperone of HSP70 [18,19]. In the adverse environment, it can complete the correct folding of protein, maintain the stability of peptide chain, and prevent cell damage caused by environmental stress [20]. Some studies have shown that DnaJ protein plays an important role in the life activities of plants to cope with environmental stress [21]. Therefore, it provides a theoretical basis for the selection of DnaJ gene as a marker for drought resistance identification of maize.

Conclusions
The marker DnaJ gene has many advantages in identifying drought resistance. The method is simple. It can identify the drought resistance of Maize by qRT-PCR alone, and does not need to combine with other characters and indexes. Accurate identification. From the results of this experiment, we can see that the expression level of DnaJ gene has a significant positive correlation with the drought resistance index IDP of different maize cultivars, which is consistent with the identification results of the field direct identification method widely used at present. It can be used to identify maize hybrids, such as Nongdan 476, Zhongxin 978 and maize inbred lines, such as 8112, zong31 and Mo17. Flexible identification period. It can be identified at seedling stage, flare stage, tasseling stage and filling stage. The qRT-PCR method based on DnaJ gene will provide an advanced technology for the identification of maize drought resistance.

Transcriptome Sequencing Materials
Two maize cultivars with contrasting drought sensitivity (tolerant Nongdan 476 and sensitive Zhongxin 978) were used in this experiment. Seeds of the two maize hybrid cultivars were provided by the North China Key Laboratory for Crop Germplasm Resources of Education Ministry ( Hebei Agricultural University, China). The experiment was conducted on May 2018 in a drought-resistant shed at Qing Yuan, Baoding, Hebei province, China (N 38°79′, E115°56′). The area of the experiment plot was 24m 2 , 60cm row spacing and 30cm plant spacing. Seeds of Nongdan 476 and Zhongxin 978 were sowed by double-grain hole with 6cm depth on the plots fertilized with compound fertilizer 512 kg/hm 2 . In this experiment, the normal watering control group and water stress treatment group were set up for the two experimental materials at seedling stage, flare stage, tasseling stage and filling stage, respectively.

Reference material
Twelve maize cultivars such as Xianyu 335, Nonghua 101, Jixiang 1 were selected as control samples. The drought resistance index and drought resistance are shown in Table 5. For twelve maize materials, a normal watering control group and a water stress treatment group were respectively set. The leaves at the seedling stage are used as experimental materials, RNA is extracted, qRT-PCR analysis were carried out , and the drought resistance index of gene expression was calculated using marker genes to verify the drought resistance of maize.

Verification materials
Forty identification materials were selected for stress treatment at seedling stage, of which forty were hybrids promoted in production. Maize seedlings grow under normal conditions until the three leaves are fully unfolded. Then, forty identification materials were subjected to drought stress treatment for 7 days. Half of the plants grew under sufficient water conditions (control group), the remaining plants were subjected to drought stress, and the soil moisture content did not exceed 50% (treatment group). After 7 days of treatment, the leaves treated with drought at the seedling stage were taken as experimental materials. RNA was extracted, and fluorescence quantification was performed. The drought resistance of maize was determined by marker gene.

Measurement of Soil Relative Moisture Content and Sampling
The relative moisture content of maize was measured by measuring the relative moisture content of the soil in the two experimental fields of normal irrigation and water stress. The relative moisture content of the soil in the normal irrigation control group and the moisture stress treatment group was 70-80% and 15-20% respectively. The relative soil moisture content (RSWC) of one meter underground was monitor by soil moisture meter ( Zhejiang Top Cloud-Agri Technology CO. Ltd., Zhejiang; China). In the water stress treatment group, the maize plants were treated with drought at the seedling stage, flare stage and the first 10 days before flowering stage, and the plants were treated with drought at the filling stage from pollination. After the soil moisture content was lower than 20% and lasted for 7 days, the top leaves were collected from the control and drought stress treated plants, frozen immediately with liquid nitrogen, stored in a refrigerator at -80 ℃, and analyzed for transcriptome. Each treatment was replicated three times.

RNA Extraction, cDNA Library Construction and Transcriptome Sequencing
Total RNA of the leaf samples was isolated from non-stressed and stressed leaves of the two maize hybrid cultivars using Trizol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer`s protocols. The RNA was purified by the treatment of RNeasy column (QIAGEN, Pudong, Shanghai, China) to remove genomic DNA. The concentration of RNA was detected by NanoDrop 1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE, USA). and the quality of extracted RNA was detected by 1% agarose gel electrophoresis. According to Illumina standard cDNA library , a kit was constructed to construct a chain specific library (on an Illumina Hiseq Xten platform, San Diego, CA, USA), which was sequenced by Novogene Bioinformatics Technology Co. Ltd. (Beijing, China).

Processing, Mapping of Sequencing Reads and Gene Expression Quantification
Raw data (raw reads) generated by the Illumina HiSeq 2000 system contains low-quality sequences with splices. In order to ensure the quality of information analysis, We need to get clean data. In this step, clean data (clean reads) were obtained by removing the sequence with N-base (n indicates that the base information can not be determined), removing the connector sequence in reads, removing the low-quality base (Q < 20), and removing the base whose tail quality value is less than 20 using the sliding window method (the window size is 5 bp), so as to obtain clean data. These high quality reads were used all the subsequent analyses. All these clean reads were then mapped to the maize reference genome sequence (B73 RefGen_v3), Tophat 2.0.12 software was used to compare the filtered data [22]. Reads that were compared to known transcriptome and partial reads that were compared were further analyzed and annotated. For functional annotation, the quality reads were used for BLAST(basic local alignment search tool) alignment and annotation against non-redundant protein sequence database (Nr) (https://www.ncbi.nlm.nih.gov/), Swiss-port (a manually annotated and reviewed protein sequence database) (https://web.expasy.org/docs/swiss-prot); Clusters of Orthologous Groups (COG) (https://www.ncbi.nlm.nih.gov/COG/) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg) [23]. Gene expression levels were calculated and standardized gene expression levels were expressed as RPKM (reads per kilobase of transcript per million mapped reads) [24].

Differentially Expresses Genes (DEGs) Library Construction and Differential Analysis
The DESeq R package (1.10.1) [25] was used to analyze the differential expression of genes [26]. In order to get the genes with significant difference, the screening condition was P-value < 0.05 (P was the adjusted p value < 0.05), and the multiple of difference |log2FC|>1. According to the RPKM value of the differential genes, and P-value of each contrast corrected for multiplicity using the Benjamini and Hochberg method [27]. The heat map of their expression quantity in each sample was drawn.

Quantitative real time-PCR (qRT-PCR) Analysis
In order to verify the expression level of the gene DNAJ gene detected by Illumina RNA-seq. In this experiment, C1000 (CFX96 Real-time System) Thermal Cycler (Bio-Rad) was used for quantitative real-time PCR (qRT-PCR). Using 1 μg of RNA as a template, perform reverse transcription to 20 μl according to the instructions of the HiFiscript cDNA Synthesis Kit (CWBIO, Beijing, China), and perform qRT-PCR using the reverse transcribed cDNA as a template. In this experiment, Primer Premier 5 Designer (Premier Biosoft International, Palo Alto, CA, USA) was used to design specific primers for differentially expressed genes of the DnaJ gene, and the results of the transcriptome were verified. The maize gene GAPDH (accession no.X07156) with stable gene expression was selected as an internal reference gene. The qTR-PCR reaction system includes: 2 μl of template cDNA , 0.5 µl of forward primer (50 pmol), 0.5 µl of reverse primer (50 pmol), and 10 µl of SYBR Green mix (TOYOBO, Japan) in a total reaction volume of 20 µl. Each sample had three technical replicates.. The relative mRNA abundance was calculated according to the 2 −ΔΔCT method [28].

Statistical Data Processing and Analysis Methods
The measured data are collected and processed uniformly by Microsoft Excel 2013.
Expression Drought Resistance Coefficient (DCE) formula: DCE = water stress expression amount÷ control expression amount; Expression Drought Resistance Index (DIE) formula: DIE = (DCE × water stress expression amount) ÷ average water stress expression amount of all maize cultivars. According to the 5-level classification standard of yield drought resistance index, ≥ 1.20 is extremely strong (HR); 1.01-1.19 is strong (R); 0.81-1.00 is medium (MR); 0.60-0.80 is weak (s); and ≤ 0.60 is extremely weak (HS) to determine the 5-level classification standard of expression drought resistance index.